Towards a Radiology Patient Portal Corey W Arnold,1 Mary Mcnamara,1 Suzie El-Saden,2 Shawn Chen,1 Ricky K Taira,1 Alex a T Bui1

Total Page:16

File Type:pdf, Size:1020Kb

Towards a Radiology Patient Portal Corey W Arnold,1 Mary Mcnamara,1 Suzie El-Saden,2 Shawn Chen,1 Ricky K Taira,1 Alex a T Bui1 Research and applications Imaging informatics for consumer health: towards a radiology patient portal Corey W Arnold,1 Mary McNamara,1 Suzie El-Saden,2 Shawn Chen,1 Ricky K Taira,1 Alex A T Bui1 1Medical Imaging Informatics, ABSTRACT look up health information online verified it with Department of Radiological Objective With the increased routine use of advanced their physicians.7 Sciences, University of fi California–Los Angeles, imaging in clinical diagnosis and treatment, it has Several bene ts of tailored information within Los Angeles, California, USA become imperative to provide patients with a means to patient portal applications have been demon- – 2Department of Imaging view and understand their imaging studies. We illustrate strated,8 10 including equipping patients with Services, Greater Los Angeles, the feasibility of a patient portal that automatically vetted, higher quality information regarding their VA Medical Center, Los structures and integrates radiology reports with disease or condition; and facilitating access to their Angeles, California, USA corresponding imaging studies according to several underlying medical records. However, little work Correspondence to information orientations tailored for the layperson. has been done to make the full range of radiology Dr Corey W Arnold, Medical Methods The imaging patient portal is composed of content—imaging and text—available to patients in Imaging Informatics, an image processing module for the creation of a an understandable format. This lack is in spite of Department of Radiological Sciences, University of timeline that illustrates the progression of disease, a the fact that radiology reports and images consti- California–Los Angeles, 924 natural language processing module to extract salient tute a significant amount of the evidence used in Westwood Blvd Ste 420, Los concepts from radiology reports (73% accuracy, F1 score diagnosis and treatment assessment. Even though Angeles, CA 90024, USA; of 0.67), and an interactive user interface navigable by radiology test results are one of the most difficult [email protected] an imaging findings list. The portal was developed as a portions of the clinical record for lay people to 11 Received 1 November 2012 Java-based web application and is demonstrated for understand, they are one of the most frequently Revised 9 May 2013 patients with brain cancer. accessed pieces of information via patient portals Accepted 15 May 2013 Results and discussion The system was exhibited at when available.12 This suggests the need for new Published Online First an international radiology conference to solicit feedback methods of sharing radiology information with 5 June 2013 from a diverse group of healthcare professionals. There patients. was wide support for educating patients about their One possibility for bridging consumers’ under- imaging studies, and an appreciation for the informatics standing of illness with professional disease models tools used to simplify images and reports for consumer is the use of an ‘interpretive layer’ between interpretation. Primary concerns included the possibility clinically-generated information and consumer- of patients misunderstanding their results, as well as centric disease explanations. Such a layer would worries regarding accidental improper disclosure of potentially enable lay patients to construct more medical information. accurate mental models of health, form effective Conclusions Radiologic imaging composes a search queries, navigate medical information significant amount of the evidence used to make systems, understand the information found within diagnostic and treatment decisions, yet there are few health documents, and apply the information to tools for explaining this information to patients. The their personal situations appropriately.13 In this proposed radiology patient portal provides a framework work we utilize the concept of interpretive layers, for organizing radiologic results into several information and describe a methodology for automatically com- orientations to support patient education. bining radiology data with educational information for the patient, presented through a web-accessible portal. INTRODUCTION BACKGROUND AND SIGNIFICANCE The number of patients accessing health informa- Towards satisfying patients’ wishes for access to tion online continues to rise,1 and being diagnosed records and better knowledge resources, govern- with cancer has been shown to increase the amount ment policy has been developed to provide incen- – of time an individual searches for information.2 4 tives for institutions utilizing patient portals in However, the popularity of a website is not always order to promote usage.14 The US Department of indicative of its quality.5 The dearth of quality Health and Human Services believes that such material online is reflected in the Health portals will not only increase patient access to Information National Trends Survey (HINTS), information, but allow patients to become more which found that Americans feel that online cancer active in their care. This sentiment is also reflected information is inadequate. Of those surveyed, 69% in a recent Institute of Medicine Report, which did not have a website they especially liked for emphasizes the importance of patient portals in a cancer information, emphasizing the need for continuously learning healthcare system.15 With 6 To cite: Arnold CW, trusted information resources. With the quality of this additional motivation, patient portal deploy- McNamara M, El-Saden S, sources in question, patients thus often bring up ment and use is expected to become common- et al. J Am Med Inform information they find online with their doctor; one place.16 In point of fact, the Health Level 7 (HL7) – Assoc 2013;20:1028 1036. study found that up to 90% of respondents who International Context-Aware Knowledge Retrieval 1028 Arnold CW, et al. J Am Med Inform Assoc 2013;20:1028–1036. doi:10.1136/amiajnl-2012-001457 Research and applications standard now provides a technical specification for integrating in radiologic interpretations31 32; a temporal orientation that electronic health records and personal health records with exter- shows the evolution of disease via imaging; and a source orien- nal information resources, and is increasingly being adopted by tation that allows patients to review an annotated version of – – vendors and information providers.17 19 their radiology reports.33 36 These three perspectives allow a Previous studies have found that despite the rising tendency user to navigate their radiologic information, allowing for the of patients to search for and access health information online, selective drilling down to the original image interpretations. they are often discouraged by the information they find as it is Figure 1 shows the four main components of our radiology frequently too general to elucidate the specifics of an indivi- portal interface: (1) a panel showing a patient’s ‘salient’ imaging – dual’s disease or treatment.1257 Notably, patients’ information findings, organized in reverse chronological order (figure 1A); needs are not limited to general knowledge, but also encompass (2) an information panel providing patient-oriented explana- access to their underlying medical records and the content tions of imaging techniques, disease concepts, and salient image within them.20 Indeed, receiving (accurate) information relevant findings (figure 1B); (3) an interactive panel showing only key to one’s cancer diagnosis has been shown to increase patient slices from patient imaging studies and associated extracted find- involvement in decision-making,8 and to enhance satisfaction ings from radiology reports (figure 1C); and (4) a study viewer with treatment options.9 Additionally, giving patients access to displaying the full image series with an annotated conclusion personalized health information can improve communication section from the corresponding report (figure 1D). Interactions between family members, and between patients and provi- with the portal are designed to be driven by the imaging find- ders.910The latter is especially important as it has been esti- ings list. From the list, a user may click on a finding of interest, mated that patients remember approximately only half of the which triggers the information panel to display a lay description information presented in a conversation with their physician.21 of the finding with an annotated illustration. In addition, click- Prior work shows that patient-oriented language is preferred ing a finding ‘activates’ imaging studies in a patient’s record by by patients when receiving abnormal radiology results,22 but graphically highlighting studies where the finding was noted by professional tools to explain medical concepts use expert lan- the radiologist. At any point, a user may click on a key slice guage, much of which patients do not understand.23 As such, from an imaging study to launch the study viewer. patients who do request copies of radiology reports and images generally receive this information with little or no additional System architecture and components explanatory material, and turn to their healthcare providers for The system architecture is shown in figure 2. Patients seen at the explanations. This scenario is sub-optimal in that some of the oncology clinic are pre-identified by a clinician, and on request, resultant questions could be answered with a suitable online our portal server fetches the required patient information information resource.
Recommended publications
  • MEDICAL IMAGING INFORMATICS: Lecture # 1
    MEDICAL IMAGING INFORMATICS: Lecture # 1 Basics of Medical Imaggging Informatics: Estimation Theory Norbert Schuff Professor of Radiology VA Medical Center and UCSF [email protected] UC Medical Imaging Informatics 2011 Nschuff SF VA Course # 170.03 Department of Slide 1/31 Radiology & Biomedical Imaging What Is Medical Imaging Informatics? • Signal Processing – Digital Image Acquisition – Image Processing and Enhancement • Data Mining – Computational anatomy – Statistics – Databases – Data-mining – Workflow and Process Modeling and Simulation • Data Management – Picture Archiving and Communication System (PACS) – Imaging Informatics for the Enterprise – Image-Enabled Electronic Medical Records – Radiology Information Systems (RIS) and Hospital Information Systems (HIS) – Quality Assurance – Archive Integrity and Security • Data Visualization – Image Data Compression – 3D, Visualization and Multi -media – DICOM, HL7 and other Standards • Teleradiology – Imaging Vocabularies and Ontologies – Transforming the Radiological Interpretation Process (TRIP)[2] – Computer pute -Aided D etectio n a nd Diag nos is (C AD ). – Radiology Informatics Education •Etc. UCSF Department of VA Radiology & Biomedical Imaging What Is The Focus Of This Course? Learn using computational tools to maximize information for knowledge gain: Pro-active Improve Data Refine collection Model Measurements knowledge Image Model Extract Compare information with Re-active model UC Medical Imaging Informatics 2009, Nschuff SF VA Course # 170.03 Department of Slide 3/31
    [Show full text]
  • Kareo User Manual
    Kareo User Manual Table Of Contents 1. GET STARTED ............................................................................................................................................................................................. 1 1.1 Installation ................................................................................................................................................................................... 1 1.1.1 System Requirements .........................................................................................................................................................................1 1.1.2 Download and Install Kareo ............................................................................................................................................................. 2 1.1.3 Software Updates ............................................................................................................................................................................... 2 1.2 User Login .................................................................................................................................................................................... 3 1.2.1 Kareo Login with User ID/Password ............................................................................................................................................... 3 1.2.2 Password Change ...............................................................................................................................................................................
    [Show full text]
  • AI in Medical Imaging Informatics: Current Challenges and Future Directions
    This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/JBHI.2020.2991043, IEEE Journal of Biomedical and Health Informatics > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 1 AI in Medical Imaging Informatics: Current Challenges and Future Directions A. S. Panayides, Senior Member, IEEE, A. Amini, Fellow, IEEE, N.D. Filipovic, IEEE, A. Sharma, IEEE, S. A. Tsaftaris, Senior Member, IEEE, A. Young, IEEE, D. Foran, IEEE, N. Do, S. Golemati, Member, IEEE, T. Kurc, K. Huang, IEEE, K. S. Nikita, Fellow, IEEE, B.P. Veasey, IEEE Student Member, M. Zervakis, Senior Member, IEEE, J.H. Saltz, Senior Member, IEEE, C.S. Pattichis, Fellow, IEEE Abstract—This paper reviews state-of-the-art research I. INTRODUCTION solutions across the spectrum of medical imaging informatics, discusses clinical translation, and provides future directions for advancing clinical practice. More specifically, it summarizes EDICAL imaging informatics covers the application of advances in medical imaging acquisition technologies for different M modalities, highlighting the necessity for efficient medical data information and communication technologies (ICT) to medical management strategies in the context of AI in big healthcare data imaging for the provision of healthcare services. A wide- analytics. It then provides a synopsis of contemporary and spectrum of multi-disciplinary medical imaging services have emerging algorithmic methods for disease classification and evolved over the past 30 years ranging from routine clinical organ/ tissue segmentation, focusing on AI and deep learning practice to advanced human physiology and pathophysiology.
    [Show full text]
  • Building Blocks for a Clinical Imaging Informatics Environment
    Building blocks for a clinical imaging informatics environment Marc D Kohli, MD1 Paul G. Nagy, PhD2 Max Warnock2 Mark Daly, BS2 Christopher Toland2 Chris Meenan, BS2 1 – Department of Radiology, Indiana University School of 550 University Blvd Indianapolis, IN 46202 2 - From the Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 22 S. Greene St., Baltimore, MD. Address correspondence to P.G.N. ([email protected]). Phone: (410) 328-6301 Fax: (410) 328-0641 Index Terms: software reuse, HL7, DICOM, Mirth, open-source, imaging informatics, informatics Abstract Over the past 10 years, imaging informatics has been driven by the widespread adoption of radiology information and picture archiving and communication and speech recognition systems. These three tools are intuitive to most radiologists as they replicate familiar paper and film workflow. So what is next? The next generation of applications will be built with moving parts that work together to satisfy advanced use cases without replicating databases and without requiring fragile, intense synchronization from clinical systems. We provide blueprints for addressing common clinical, educational, and research related problems. This paper is the result of identifying common components in the construction of over two dozen clinical informatics projects developed at the University of Maryland Radiology Informatics Research Laboratory. The systems outlined are intended as a strong foundation rather than an exhaustive list of possible extensions. Background Software reuse is a philosophy that makes stored information more accessible and flexible, facilitating creation of novel uses of existing data. Before examining software reuse within healthcare, we present online-travel an example of the higher-level integration that we strive toward.
    [Show full text]
  • Imaging and Structural Informatics
    9 Imaging and Structural Informatics JAMES F. B RINKLEY AND ROBERT A. GREENES 9.1 Introduction As is evident to anyone who has had an X-ray, a magnetic resonance imaging (MRI) exam, or a biopsy, images play a central role in the health care process. In addition, images play important roles in medical communication and education, as well as in research. In fact much of our recent progress, particularly in diagnosis, can be traced to the availability of increasingly sophisticated images that not only show the structure of the body in incredible detail but also show the function. Although there are many imaging modalities, images of all types are increasingly being converted to or initially acquired in digital form. This form is more or less the same across all imaging modalities. It is therefore amenable to common image-processing methodologies for enhancement, analysis, display, and storage. Because of the ubiquity of images in biomedicine, the increasing availability of images in digital form, the rise of high-powered computer hardware and networks, and the commonality of image-processing solutions, digital images have become a core data type that must be considered in many biomedical informatics applications. Therefore, this chapter is devoted to a basic understanding of this core data type and many of the image-processing operations that can be applied to it. Chapter 18, on the other hand, describes the integration of images and image processing in various applications, particularly those in radiology since radiology places the greatest demands on imaging methods. The topics covered by this chapter and Chapter 18 are generally part of biomedical imaging informatics (Kulikowski, 1997), a subfield of biomedical informatics that has arisen in recognition of the common issues that pertain to all image modalities and applications once the images are converted to digital form.
    [Show full text]
  • 9. Biomedical Imaging Informatics Daniel L
    9. Biomedical Imaging Informatics Daniel L. Rubin, Hayit Greenspan, and James F. Brinkley After reading this chapter, you should know the answers to these questions: 1. What makes images a challenging type of data to be processed by computers, as opposed to non-image clinical data? 2. Why are there many different imaging modalities, and by what major two characteristics do they differ? 3. How are visual and knowledge content in images represented computationally? How are these techniques similar to representation of non-image biomedical data? 4. What sort of applications can be developed to make use of the semantic image content made accessible using the Annotation and Image Markup model? 5. Describe four different types of image processing methods. Why are such methods assembled into a pipeline when creating imaging applications? 6. Give an example of an imaging modality with high spatial resolution. Give an example of a modality that provides functional information. Why are most imaging modalities not capable of providing both? 7. What is the goal in performing segmentation in image analysis? Why is there more than one segmentation method? 8. What are two types of quantitative information in images? What are two types of semantic information in images? How might this information be used in medical applications? 9. What is the difference between image registration and image fusion? Given an example of each. 1 9.1. Introduction Imaging plays a central role in the healthcare process. Imaging is crucial not only to health care, but also to medical communication and education, as well as in research.
    [Show full text]
  • Top 20 Ehr Software
    TOP 20 EHR SOFTWARE C M CONVERTED MEDIA TOP 20 EHR SOFTWARE 1 AdvancedMD AdvancedEHR 11 Allscripts Allscripts Professional EHR 2 Cerner Cerner Ambulatory EHR 12 CareCloud CareCloud Charts 3 athenahealth athenahealth EHR 13 CureMD All in One EHR 4 Epic Epic EHR 14 Practice Velocity VelociDoc EHR Azalea Health 5 Practice Fusion Practice Fusion EHR 15 Azalea EHR Innovations 6 Kareo Kareo Clinical 16 ReLi Med Solutions ReLiMed EMR 7 Henry Schein MicroMD EMR 17 MedEZ MedEZ 8 drchrono drchrono EHR 18 iSALUS Healthcare OfficeEMR 9 NextGen Healthcare NextGen Healthcare EHR 19 ChartLogic ChartLogic EMR Modernizing 10 EMA 20 ICANotes ICANotes EHR Medicine C M CONVERTED MEDIA EHR IN PRACTICE HOW THESE RANKINGS WERE GENERATED This ranking was determined using a number of factors including industry standing, public opinion of software, social media presence, and available software features relevant to the needs of a small business. This ranking should serve as a rough estimate of software suitability, and more in-depth analysis can be taken below or by using our EHR software comparison. C M CONVERTED MEDIA SHORTLISTING EHR VENDORS CHECKLIST Research EHR employed by similar sized practices in 1 6 Produce an RFI document and send to vendor shortlist the same specialty Identify market leading solutions which offer some 2 7 Narrow shortlist based on RFI responses support in your specialty Leverage professional network for recommendations Compile requirements and business processes in an 3 8 based on their experience RFP document Narrow shortlist based
    [Show full text]
  • Medical Imaging Informatics
    Editorial Casimir A. Kulikowski1 Editorial Reinhold Haux2 Editors Medical Imaging Informatics 1 Department of Computer Science Rutgers - The State University of New Jersey New Brunswick, New Jersey, USA 2 Department of Medical Informatics University of Heidelberg Heidelberg, Germany and University for Health Informatics and Technology Tyrol Innsbruck, Austria The 2002 Yearbook of Medical multiple underlying biological levels Informatics takes as its theme the topic (cellular, molecular, atomic) leading to of Medical Imaging Informatics. The the definition of structural informatics visual nature of so much critical [5], and the development of a Founda- information in the practice, research, tional Model of Anatomy [6]. Mean- and education of medicine and health while, knowledge representations for care would suggest that computer-based integrating multimodal image inter- imaging and its related fields of graphics pretations [7], methods for modeling and visualization should be central to the elastically deformable anatomical practice of medical informatics. Yet, objects [8], integrated segmentation historically, this has not usually been the and visualization systems [9], knowl- case. The need for technological sub- edge-based methods [10], and model- specialization on the part of imaging driven systems for surgery and educa- researchers and the frequently opposite tion [11] have been gradually helping tendency towards generality of informa- renew connections between imaging and tion systems studied and developed by mainstream informatics work. Encour- informatics researchers may have aging further productive collaborations contributed to an increasing separation between researchers in imaging and between the fields in the period from the informatics was one of our motivations 1970’s to the 1990’s. in the choice of Medical Imaging Infor- matics as the theme for this Yearbook.
    [Show full text]
  • Imaging Informatics
    Imaging Informatics: Essential Tools for the Delivery of Imaging Services David S. Mendelson, MD, Daniel L. Rubin, MD, MS There are rapid changes occurring in the health care environment. Radiologists face new challenges but also new opportunities. The purpose of this report is to review how new informatics tools and developments can help the radiologist respond to the drive for safety, quality, and efficiency. These tools will be of assistance in conducting research and education. They not only provide greater efficiency in traditional operations but also open new pathways for the delivery of new services and imaging technologies. Our future as a specialty is dependent on integrating these informatics solutions into our daily practice. Key Words: Radiology Informatics; PACS; RadLex; decision support; image sharing. ªAUR, 2013 he health care environment is undergoing rapid A BRIEF LOOK BACKWARD change, whether secondary to health care reform Radiology information systems (RIS) and picture archiving (1–3), natural organic changes, or accelerated T and communications systems (PACS), commonplace tools, technological advances. The economics of health care, are relatively recent developments. In 1983, the first American changes in the demographics of our population, and the College of Radiology (ACR)–National Electrical Manu- rapidly evolving socioeconomic environment all contribute facturers Association (NEMA) Committee met to develop to a world that presents the radiologist with new challenges. the ACR-NEMA standard (5), first published in 1985. In New models of health care, including accountable care 1993, the rapid rise in the number of digital modalities organizations, are emerging (4) . Our profession must adapt; and the parallel development of robust networking technol- the traditional approach to delivering imaging services may ogy prompted the development of digital imaging and not be viable.
    [Show full text]
  • Ecw Enterprise Patient Portal Mandatory
    ENTERPRISE PATIENT PORTAL V2.1 MANDATORY DISCLOSURES December 2020 CONFIDENTIAL © eClinicalWorks, 2020. All rights reserved. Enterprise Patient Portal V2.1 Mandatory Disclosures CONTENTS 1. MANDATORY DISCLOSURES ____________________________________________________ 3 1.1. Add on Service: eClinicalWorks Enterprise Patient Portal ____________________________________ 3 §170.315(d)(1) - Authentication, Access Control, and Authorization ________________________________ 4 §170.315(d)(2) - Auditable Events and Tamper-Resistance __________________________________________ 4 §170.315(d)(3) - Audit Reports ________________________________________________________________________ 5 §170.315(d)(5) - Automatic Access Time-Out ________________________________________________________ 5 §170.315(d)(7) - End-User Device Encryption ________________________________________________________ 6 §170.315(d)(9) - Trusted Connection _________________________________________________________________ 6 §170.315(e)(1) - View, Download, and Transmit to Third-Party ______________________________________ 6 §170.315(e)(2) - Secure Messaging ___________________________________________________________________ 7 §170.315(e)(3) - Patient Health Information Capture ________________________________________________ 7 §170.315(g) (4-5) - Quality Management System (QMS) and Accessibility-Centered Design (ACD) __________________________________________________________________________________________ 8 §170.315(g)(6) - Consolidated CDA Creation Performance __________________________________________
    [Show full text]
  • Hospital Capabilities to Enable Patient Electronic Access to Health Information, 2019
    ONC Data Brief No. 55 | June 2021 Hospital Capabilities to Enable Patient Electronic Access to Health Information, 2019 Christian Johnson, MPH & Wesley Barker, MS A patient’s access to their health information is required and reinforced through multiple federal policy levers. The Office of the National Coordinator for Health Information Technology (ONC) Health IT Certification Program certifies health information technology (IT) that enables patient access to their electronic medical record (1). Starting in 2014, hospitals were incentivized by the Centers for Medicare & Medicaid Services (CMS) Electronic Health Record (EHR) Incentive Program to adopt certified health IT that enabled patients to electronically view, download, and transmit their health information. In 2019, CMS required hospitals to provide their patients with the ability to access their health information via an application programming interface (API) using an app of their choice (2). This data brief presents the latest national estimates on the proportion of U.S. hospitals that enabled patient electronic access to their health information. HIGHLIGHTS Seven in 10 hospitals enabled inpatients to access their health information using mobile or other software applications. In 2019, nearly all hospitals enabled patients to electronically view their health information using a portal. Three in four hospitals enabled their inpatients to view their clinical notes in their patient portal. Small, rural, independent, and Critical Access hospitals enabled inpatient access to health information at lower rates compared to their counterparts. 1 ONC Data Brief | No. 55 | June 2021 Hospital Capabilities to Enable Patient Electronic Access to Health Information, 2019 Seven in ten hospitals enabled inpatients to access their health information using an app in 2019.
    [Show full text]
  • Measuring the Impact of Patient Portals: What the Literature Tells Us
    C A LIFORNIA HEALTHCARE FOUNDATION Measuring the Impact of Patient Portals: What the Literature Tells Us Prepared for CALIFORNIA HEALT H CARE FOUNDATION by Seth Emont, Ph.D., M.S. May 2011 About the Author Seth Emont, Ph.D., M.S., is the principal of White Mountain Research Associates, L.L.C. He has provided ongoing program and evaluation technical assistance for a number of national and statewide initiatives, including research and evaluation of clinical care delivery and quality improvement, pediatric asthma management, diabetes management, self-management support, patient- and family-centered care, childhood obesity, end-of-life care, tobacco and substance use, and eHealth. About the Foundation The California HealthCare Foundation works as a catalyst to fulfill the promise of better health care for all Californians. We support ideas and innovations that improve quality, increase efficiency, and lower the costs of care. For more information, visit us online at www.chcf.org. ©2011 California HealthCare Foundation Contents 2 I. Introduction 3 II. Background — EHR and Patient Portal Adoption Benefits of Portals and EHRs Barriers and Incentives 5 III. Research on Patient-Level Measures Volume and Demographics of Users Opinions and Concerns of Users Patients with Chronic Illness Focus on Young People 10 IV. Research Linking Portals with Clinical Outcomes and Operational Efficiency Phone Volume and Web Messaging Availability Impact on Types of Patient Contacts Patient-Physician Messaging and Visit/Phone Rates Patient-Physician Messaging and Chronic Care Patient-Physician Messaging and Provider Productivity Cost-Savings Estimates 13 V. Conclusions 14 Appendix: Summary of Study Findings 17 Endnotes I. Introduction PATIENT P ORTALS C AN OFFER IM P ORTANT benefits to patients and provider organizations.
    [Show full text]